Synthesis of topologically-constrained water reuse network using swarm intelligence
The sustainability of water resources is one of the major concerns of the world population. As such, industries are finding ways to minimize the water withdrawals and to reduce the water pollution through efficient use of water supplies. Process water integration has focused on the reduction of the...
Saved in:
Main Author: | |
---|---|
Format: | text |
Language: | English |
Published: |
Animo Repository
2006
|
Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/etd_masteral/3534 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10372/viewcontent/CDTG004356_P.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
Language: | English |
id |
oai:animorepository.dlsu.edu.ph:etd_masteral-10372 |
---|---|
record_format |
eprints |
spelling |
oai:animorepository.dlsu.edu.ph:etd_masteral-103722023-10-20T00:39:54Z Synthesis of topologically-constrained water reuse network using swarm intelligence Hul, Seingheng The sustainability of water resources is one of the major concerns of the world population. As such, industries are finding ways to minimize the water withdrawals and to reduce the water pollution through efficient use of water supplies. Process water integration has focused on the reduction of the amount of water used and water discharged. Water integration is done to determine both the minimum fresh water budget and wastewater released. The water network needed to get this minimum water usage was determined by establishing the reuse scheme, from the source streams to feed the sink streams. A procedure for designing reuse networks with topological, network complexity and stream matching constraints was developed. The procedure used particle swarm optimization (PSO) enhanced with genetic mutator. The result achieved by PSO was compared with commercial genetic algorithms (GA) package. Four main case studies with sub-cases were used to test PSO. The freshwater saving achieved by PSO and commercial GA package with the same number of function evaluations ranged from 6 - 54% and 1 - 43%, respectively. The amount of water saving varies depending on the cases conducted. PSO provided a better result than the commercial GA package. The PSO algorithm was further improved by introducing mutation to integer variables and seeding strategy. 2006-01-01T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etd_masteral/3534 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10372/viewcontent/CDTG004356_P.pdf Master's Theses English Animo Repository Swarm intelligence Mathematical optimization Genetic algorithms Water reuse Chemical Engineering |
institution |
De La Salle University |
building |
De La Salle University Library |
continent |
Asia |
country |
Philippines Philippines |
content_provider |
De La Salle University Library |
collection |
DLSU Institutional Repository |
language |
English |
topic |
Swarm intelligence Mathematical optimization Genetic algorithms Water reuse Chemical Engineering |
spellingShingle |
Swarm intelligence Mathematical optimization Genetic algorithms Water reuse Chemical Engineering Hul, Seingheng Synthesis of topologically-constrained water reuse network using swarm intelligence |
description |
The sustainability of water resources is one of the major concerns of the world population. As such, industries are finding ways to minimize the water withdrawals and to reduce the water pollution through efficient use of water supplies. Process water integration has focused on the reduction of the amount of water used and water discharged. Water integration is done to determine both the minimum fresh water budget and wastewater released. The water network needed to get this minimum water usage was determined by establishing the reuse scheme, from the source streams to feed the sink streams. A procedure for designing reuse networks with topological, network complexity and stream matching constraints was developed. The procedure used particle swarm optimization (PSO) enhanced with genetic mutator. The result achieved by PSO was compared with commercial genetic algorithms (GA) package. Four main case studies with sub-cases were used to test PSO. The freshwater saving achieved by PSO and commercial GA package with the same number of function evaluations ranged from 6 - 54% and 1 - 43%, respectively. The amount of water saving varies depending on the cases conducted. PSO provided a better result than the commercial GA package. The PSO algorithm was further improved by introducing mutation to integer variables and seeding strategy. |
format |
text |
author |
Hul, Seingheng |
author_facet |
Hul, Seingheng |
author_sort |
Hul, Seingheng |
title |
Synthesis of topologically-constrained water reuse network using swarm intelligence |
title_short |
Synthesis of topologically-constrained water reuse network using swarm intelligence |
title_full |
Synthesis of topologically-constrained water reuse network using swarm intelligence |
title_fullStr |
Synthesis of topologically-constrained water reuse network using swarm intelligence |
title_full_unstemmed |
Synthesis of topologically-constrained water reuse network using swarm intelligence |
title_sort |
synthesis of topologically-constrained water reuse network using swarm intelligence |
publisher |
Animo Repository |
publishDate |
2006 |
url |
https://animorepository.dlsu.edu.ph/etd_masteral/3534 https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10372/viewcontent/CDTG004356_P.pdf |
_version_ |
1781418162721390592 |